• DocumentCode
    2470660
  • Title

    On process mining in health care

  • Author

    Kaymak, Uzay ; Mans, Ronny ; van de Steeg, T. ; Dierks, Meghan

  • Author_Institution
    Dept. of Inf. Syst., Eindhoven Univ. of Technol., Eindhoven, Netherlands
  • fYear
    2012
  • fDate
    14-17 Oct. 2012
  • Firstpage
    1859
  • Lastpage
    1864
  • Abstract
    With the increasing demand for health care, hospitals are looking for ways to optimize their care processes in order to increase efficiency, while guaranteeing the quality of the care. Process modeling is a crucial step for process improvement, since it provides a process model that can be analyzed and optimized. Process mining is a recent promising methodology to discover process models based on data from event logs. However, early applications of process mining to health care has produced overly complex models, which have been attributed to the complexity of the health care domain. In this paper, we argue that existing process mining methods fail to identify good process models, even for well-defined clinical processes. We identify a number of reasons for this shortcoming and discuss a few directions for extending process mining methods in order to make them more suitable for the clinical domain.
  • Keywords
    data mining; health care; medical administrative data processing; clinical domain; clinical process; event logs; health care process; health care quality; hospital; process improvement; process mining; process modeling; Anesthesia; Biomedical monitoring; Blood pressure; Data mining; Data models; Drugs; Healthcare; clinical processes; process mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4673-1713-9
  • Electronic_ISBN
    978-1-4673-1712-2
  • Type

    conf

  • DOI
    10.1109/ICSMC.2012.6378009
  • Filename
    6378009